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MLflow Tracking Server Key

Service Name: MLflow

Service Description: MLflow is an open-source platform for managing the end-to- end machine learning lifecycle. It provides tools for tracking experiments, packaging code into reproducible runs, and sharing and deploying models.

Service Address: https://mlflow.org/

Validation Type: API Auth

IP Allow list: IP restrictions can be configured at the server level depending on deployment configuration.

Secret Access Scope: Grants access to MLflow tracking server for logging parameters, metrics, artifacts, and managing experiments.

Secret Revokement URL: Does not exist (managed through server configuration)

Secret Example: mlflow-tracking-token-a1b2c3d4e5f6g7h8i9j0

Suspicious Activity Investigation Instructions:

  • Review MLflow tracking server logs for unusual access patterns or experiment modifications
  • Check for unexpected experiment creations or model registrations
  • Monitor for unusual artifact uploads or downloads
  • Examine tracking server access logs for unauthorized IP addresses
  • Look for abnormal usage patterns such as high-volume requests or off-hours activity

Mitigation Instructions:

  • Rotate the tracking server authentication token by updating the server configuration

  • Update authentication settings in the MLflow tracking server configuration

  • Remove the compromised token from authorized credentials
  • Implement more restrictive access controls on the MLflow tracking server
  • Consider implementing additional authentication mechanisms such as OAuth or

LDAP

  • Review and update network access controls to limit server accessibility
  • Audit all experiments and models for unauthorized changes